GERry: A code to optimise the hunt for the electromagnetic counter-parts to gravitational wave events

O'Neill, David; Lyman, Joseph; Ackley, Kendall; Steeghs, Danny; Galloway, Duncan; Dhillon, Vik; O'Brien, Paul; Ramsay, Gavin; Noysena, Kanthanakorn; Kotak, Rubina; Breton, Rene; Nuttall, Laura; Pallé, Enric; Pollacco, Don; Ulaczyk, Krzysztof; Dyer, Martin; Jiménez-Ibarra, Felipe; Killestein, Tom; Kumar, Amit; Kelsey, Lisa; Godson, Ben; Jarvis, Dan
Bibliographical reference

Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series

Advertised on:
7
2024
Number of authors
22
IAC number of authors
1
Citations
0
Refereed citations
0
Description
The search for the electromagnetic counterparts to Gravitational Wave (GW) events has been rapidly gathering pace in recent years thanks to the increasing number and capabilities of both gravitational wave detectors and wide field survey telescopes. Difficulties remain, however, in detecting these counterparts due to their inherent scarcity, faintness and rapidly evolving nature. To find these counterparts, it is important that one optimizes the observing strategy for their recovery. This can be difficult due to the large number of potential variables at play. Such follow-up campaigns are also capable of detecting hundreds or potentially thousands of unrelated transients, particularly for GW events with poor localization. Even if the observations are capable of detecting a counterpart, finding it among the numerous contaminants can prove challenging. Here we present the Gravitational wave Electromagnetic RecovRY code (GERRY) to perform detailed analysis and survey-agnostic quantification of observing campaigns attempting to recover electromagnetic counterparts. GERRY considers the campaign's spatial, temporal and wavelength coverage, in addition to Galactic extinction and the expected counterpart light curve evolution from the GW 3D localization volume. It returns quantified statistics that can be used to: determine the probability of having detected the counterpart, identified the most promising sources, and assessed and refine strategy. Here we demonstrate the code to look at the performance and parameter space probed by current and upcoming wide-field surveys such as GOTO and VRO.